Assessment of Lifestyle Behaviour and its Association in Different Professions of Twin Cities Using Short Multidimensional Inventory Lifestyle Evaluation - Confinement (SMILE-C) Questionnaire; A Cross-sectional Survey

Abstract

Introduction: A multidimensional scale (SMILE-C) had been used during the COVID-19. This tool was developed from the original SMILE which is a self-assessed 43-item questionnaire comprising seven lifestyle domains. SMILE-C is a modified version of original SMILE consisting of 27 items and was developed to carry out a multidimensional and comprehensive assessment of lifestyle during the previous 30 days. It has been used in the western world during the COVID-19 pandemic but hasn’t been utilized in the general population of Pakistan. This study aimed at evaluating the lifestyle behavior in different professions by using SMILE-C questionnaire.

Objective: The study aims to analyze lifestyle behavior among individuals belonging to different professions in Pakistan.

Materials and methods: A survey was conducted among the general population of Pakistan living in Rawalpindi and Islamabad belonging to 5 occupations: doctor, teacher, IT specialist, banker, laborer. The survey comprised of demographic details and questions regarding lifestyle assessed through Short Multidimensional Inventory Lifestyle Evaluation- Confinement (SMILE-C) Questionnaire. The participants voluntarily filled the consent form and self-reported changes in 7 lifestyle domains. Data was analyzed using IBM® SPSS® 27. Kruskal-Wallis test and Mann-Whitney U test were used to test significance among variables

Results: The total sample size was 400, 80 from each of the five professions. Mean SMILE-C score was 82.24 in the total sample. Mean scores among professions were 81.82 ± 8.02 (doctor), 86.70 ± 8.53 (teacher), 81.06 ± 8.11 (IT specialist), 78.79 ± 11.57 (banker), 82.77 ± 12.47 (laborer), indicating that teachers had the highest score (better lifestyle). Differences in seven lifestyle domains among professions was statistically significant (p<0.001). Pairwise comparisons among them also showed significant differences in various domains.

Conclusion: Our study showed meaningful changes in lifestyle among different occupations in seven lifestyle domains, suggesting that occupation impacts lifestyle behavior in various ways. The findings highlight the importance of incorporating healthy lifestyle practices and the need for targeted lifestyle interventions to promote health in a community.

Keywords: Lifestyle, inventory, evaluation